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Luca Turchet

Publications and source records attributed to Luca Turchet.

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WebXR and Commercial Game Engines for the Metaverse: A Socio-Technical Analysis of Openness, Interoperability, and Sustainability

The Metaverse is often framed as a persistent, interoperable, and embodied network of virtual and augmented environments. Yet, most contemporary XR applications are developed through commercial game engines and distributed through proprietary app stores, creating tensions between openness and platform dependency. This paper critically examines open WebXR technologies with conventional commercial game-engine pipelines, with particular attention to XR hardware, software architectures, developer workflows, governance, ethics, interoperability, and sustainability. We argue that WebXR may provide a viable route toward a more accessible, device-independent, and institutionally sustainable Metaverse, especially for education, research, cultural heritage, prototyping, and public-interest applications. At the same time, commercial engines remain advantageous for graphically intensive, low-latency, deeply integrated, and large-scale XR products. The paper concludes that the choice should not be framed as WebXR versus engines, but as a continuum: WebXR is preferable when accessibility, interoperability, low-friction deployment, and long-term maintainability are primary goals, whereas native engines remain preferable when performance, platform-specific hardware access, and production-grade tooling dominate.

cs.CY

Security and Privacy in the Musical Metaverse: Threat Analysis and Design Implications

The Musical Metaverse (MM) introduces immersive, real-time environments for collaborative musical interaction, characterized by ultra-low-latency constraints, continuous multimodal data streams, and heterogeneous devices. These properties create a distinctive security and privacy landscape that differs significantly from conventional XR or multimedia systems. This paper presents a multi-layer threat analysis of MM ecosystems, identifying key assets including live musical content, expressive interaction data, identity and session metadata, and intellectual property. Threats are analyzed across network, application, data/AI, device, intellectual property rights, and social layers, with particular attention to risks arising from expressive and neurophysiological data, which enable inference, re-identification, and potential privacy violations. We describe a stakeholder-driven survey involving 14 participants from 13 organizations, revealing that neurophysiological data leakage and real-time stream disruption are perceived as the most critical risks, followed by intellectual property infringement and avatar impersonation. We further evaluate the suitability of existing security protocols under strict latency constraints, showing that conventional approaches such as TLS over TCP are often incompatible with real-time musical interaction, while lightweight, stream-oriented mechanisms (e.g., SRTP, DTLS) provide a more suitable balance between security and performance. Based on these findings, we derive a set of design guidelines for MM systems, emphasizing latency-aware security, differentiation of interaction paths, data minimization, and edge-centric processing. The results support a security-by-design approach that enables trust and compliance without compromising real-time performance.

cs.CR